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Media Contacts

A study by Department of Energy researchers detailed a potential method to detect the novel coronavirus

A team of collaborators from ORNL, Google Inc., Snowflake Inc. and Ververica GmbH has tested a computing concept that could help speed up real-time processing of data that stream on mobile and other electronic devices.

Research teams from the Department of Energy’s Oak Ridge National Laboratory and their technologies have received seven 2021 R&D 100 Awards, plus special recognition for a COVID-19-related project.

Oak Ridge National Laboratory researchers have created a technology that more realistically emulates user activities to improve cyber testbeds and ultimately prevent cyberattacks.

An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.

Deborah Frincke, one of the nation’s preeminent computer scientists and cybersecurity experts, serves as associate laboratory director of ORNL’s National Security Science Directorate. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

When COVID-19 was declared a pandemic in March 2020, Oak Ridge National Laboratory’s Parans Paranthaman suddenly found himself working from home like millions of others.

When Kashif Nawaz looks at a satellite map of the U.S., he sees millions of buildings that could hold a potential solution for the capture of carbon dioxide, a plentiful gas that can be harmful when excessive amounts are released into the atmosphere, raising the Earth’s temperature.

Scientists have found new, unexpected behaviors when SARS-CoV-2 – the virus that causes COVID-19 – encounters drugs known as inhibitors, which bind to certain components of the virus and block its ability to reproduce.

To better understand the spread of SARS-CoV-2, the virus that causes COVID-19, Oak Ridge National Laboratory researchers have harnessed the power of supercomputers to accurately model the spike protein that binds the novel coronavirus to a human cell receptor.